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Introduces Scientific Machine Learning, emphasizing its application in various scientific fields and the connection between machine learning and physics.
Delves into energy-saving design principles in wireless sensor networks, exploring motivating applications and intelligent algorithms for energy efficiency.
Covers feature extraction, clustering, and classification methods for high-dimensional datasets and behavioral analysis using PCA, t-SNE, k-means, GMM, and various classification algorithms.